# data file for correlation bounds
import numpy as np
m = 10 # number of linear functions with known variance
n = 5 # length of the random vector Z
A = np.array([
    [-1.4401 , -0.2568 , -0.4253 ,  0.3839 , -0.3007 ,  0.3794 ,  1.7744 ,  0.3712 ,  0.3996 ,  1.2323] ,
    [-0.1747 , -0.8338 ,  2.7900 ,  0.3703 ,  0.8218 ,  0.0185 , -0.7323 ,  1.0773 ,  0.9564 , -0.7745] ,
    [-0.5972 , -0.1770 ,  1.2684 ,  1.0716 ,  1.5609 , -0.9204 , -1.5823 ,  0.5888 ,  0.9646 , -0.6642] ,
    [-1.0254 ,  0.2775 ,  0.6665 , -0.2695 , -0.8905 , -1.3962 , -0.4194 ,  1.5121 , -0.5088 , -2.0358] ,
    [-1.5929 , -0.3059 ,  0.9112 , -0.5246 ,  0.2679 ,  0.0038 ,  0.7488 ,  0.8160 , -1.3199 ,  0.6035]])
sigma = np.array([ 4.6542 ,  1.2522 ,  4.5739 ,  1.4898 ,  0.9448 ,  1.5184 ,  1.9903 ,  3.8886 ,  1.5138 ,  2.4334])

